Injecting CO2 into subsurface formations for large-scale geological carbon sequestration requires rapid and reliable reservoir-pressure estimation for storage integrity and minimization of potential seismic activities. Although various machine- and deep-learning models have been proposed for this purpose, these models typically require numerous reservoir simulations to generate adequate training data, which can be computationally expensive and potentially can offset the acceleration in pressure prediction. This work uses a novel pseudosteady-state-based simulation (PSS-SIM) to significantly reduce training-data-generation cost while maintaining high-performance predictions of data-driven proxy models for near-real-time monitoring and control of carbon sequestration projects.
Methodology
Pseudosteady-State Pressure Contour. The applicability of fast marching method (FMM)-based simulation has been demonstrated in unconventional oil and gas reservoir and enhanced geothermal applications, both of which are characterized by lower permeability. While FMM-based simulation has been applied successfully to low-permeability reservoirs, this method has limitations with regard to applications for high-permeability reservoirs, which are typical for carbon capture and storage (CCS) applications.
